DocumentCode
1649383
Title
An efficient defect compensation scheme for multi-layer neural networks on WSI devices
Author
Yamamori, Kunihito ; Abe, Tom ; Horiguchi, Susumu ; Yoshihara, Ikuo
Author_Institution
Fac. of Eng., Miyazaki Univ., Japan
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1056
Lastpage
1061
Abstract
Discusses a high speed off-line defect compensation scheme for trained multi-layer neural networks implemented in WSI devices. Since the partial retraining scheme utilizes the redundancy of neural networks, no additional circuits are needed. The performance of the partial retraining scheme is compared with that of a back-propagation algorithm on a face image recognition problem
Keywords
compensation; face recognition; fault tolerance; generalisation (artificial intelligence); learning (artificial intelligence); multilayer perceptrons; wafer-scale integration; WSI devices; backpropagation algorithm; defect compensation scheme; face image recognition problem; multi-layer neural networks; partial retraining scheme; redundancy; wafer scale integration; Acceleration; Equations; Image recognition; Information science; Large-scale systems; Multi-layer neural network; Neural networks; Neurons; Parallel processing; Redundancy;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005622
Filename
1005622
Link To Document